metadata
license: mit
library_name: transformers
tags:
- mergekit
- merge
base_model:
- AIDC-AI/Marco-o1
- happzy2633/qwen2.5-7b-ins-v3
model-index:
- name: intelligence-cod-rag-7b-v3
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 68.98
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 34.78
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 9.82
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 3.02
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 10.68
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 35.51
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ClaudioItaly/intelligence-cod-rag-7b-v3
name: Open LLM Leaderboard
merge
my elaboration and fusion of the models has led to a surprising result that I want to share with you all. I recommend you try this merge of mine.
Demonstrates strong reasoning skills when asked questions or texts. It is useful for reasoning to formulate questions with this example "Question: How did the Moon arise in your opinion?
GGUF ClaudioItaly/intelligence-cod-rag-7b-v3-Q6_K-GGUF GUUF ClaudioItaly/intelligence-cod-rag-7b-v3-Q8_0-GGUF
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ClaudioItaly__intelligence-cod-rag-7b-v3)
| Metric |Value|
|-------------------|----:|
|Avg. |27.13|
|IFEval (0-Shot) |68.98|
|BBH (3-Shot) |34.78|
|MATH Lvl 5 (4-Shot)| 9.82|
|GPQA (0-shot) | 3.02|
|MuSR (0-shot) |10.68|
|MMLU-PRO (5-shot) |35.51|